A5103088617- Data Management and Algorithms
- Rough Sets and Fuzzy Logic
- Constraint Satisfaction and Optimization
- Complex Network Analysis Techniques
- Geographic Information Systems Studies
- Advanced Computational Techniques and Applications
- Data Mining Algorithms and Applications
- Semantic Web and Ontologies
- Bayesian Modeling and Causal Inference
- Service-Oriented Architecture and Web Services
- Opinion Dynamics and Social Influence
- Text and Document Classification Technologies
- Advanced Graph Neural Networks
- Mobile Agent-Based Network Management
- Logic, Reasoning, and Knowledge
- Network Security and Intrusion Detection
- Web Data Mining and Analysis
- Peer-to-Peer Network Technologies
- Face and Expression Recognition
- Neural Networks and Applications
- Business Process Modeling and Analysis
- Access Control and Trust
- Fuzzy Logic and Control Systems
- Industrial Technology and Control Systems
- Multi-Agent Systems and Negotiation
Chinese Academy of Sciences
2005-2024
Shenyang Institute of Automation
2020-2024
Jilin University
2013-2023
Jilin Province Science and Technology Department
2011-2023
Emory University
2023
University of Chinese Academy of Sciences
2020
Jilin Medical University
1991-2015
Ministry of Education of the People's Republic of China
2005-2012
Liaoning Technical University
2012
Changchun Normal University
2010
This paper is a survey for smart home research, from definition to current research status. First we give home, and then describe the elements, typical projects, networks status, appliances challenges at last.
Abstract Representation and reasoning with qualitative spatial relations is an important problem in artificial intelligence has wide applications the fields of geographic information system, computer vision, autonomous robot navigation, natural language understanding, databases so on. The reasons for this interest using include cognitive comprehensibility, efficiency computational facility. This paper summarizes progress representation by describing key calculi representing different types...
Detection of overlapping communities in complex networks has motivated recent research the relevant fields.Aiming this problem, we propose a Markov dynamics based algorithm, called UEOC, which means, "unfold and extract communities".In when identifying each natural community that overlaps, random walk method combined with constraint strategy, is on corresponding annealed network (degree conserving network), performed to unfold community.Then, cutoff criterion aid local function, conductance,...
In order to develop a new and effective prediction system, the full potential of support vector machine (SVM) was explored by using an improved grey wolf optimization (GWO) strategy in this study. An GWO, IGWO, first proposed identify most discriminative features for major prediction. approach, particle swarm (PSO) firstly adopted generate diversified initial positions, then GWO used update current positions population discrete searching space, thus getting optimal feature subset better...
PDF HTML阅读 XML下载 导出引用 引用提醒 复杂网络聚类方法 DOI: 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: Supported by the National Natural Science Foundation of China under Grant Nos.60496321, 60503016, 60573073, 60873149 (国家自然科学基金); High-Tech Research and Development Plan No.2006AA10Z245 (国家高技术研究发展计划(863) Complex Network Clustering Algorithms Author: Affiliation: Fund Project: 摘要 | 图/表 访问统计 参考文献 相似文献 引证文献 资源附件 文章评论...
Detecting communities from complex networks has triggered considerable attention in several application domains. Targeting this problem, a local search based genetic algorithm (GALS) which employs graph-based representation (LAR) been proposed work. The core of the GALS is mutation technique. Aiming to overcome drawbacks existing methods, concept called marginal gene proposed, and then an effective efficient method, combined with strategy on gene, also by analyzing modularity function....
Complex network theory provides a means for modeling and analyzing complex systems that consist of multiple interdependent components. Among the studies on networks, structural analysis is fundamental importance as it presents natural route to understanding dynamics, well synthesizing or optimizing functions, networks. A wide spectrum patterns networks has been reported in past decade, such communities, multipartites, bipartite, hubs, authorities, outliers, bow ties, among others. In this...
The number of the overweight people continues to rise across world. Studies have shown that being can increase health risks, such as high blood pressure, diabetes mellitus, coronary heart disease, and certain forms cancer. Therefore, identifying status in is critical prevent decrease risks. This study explores a new technique uses biochemical measurements recognize condition. A machine learning technique, an extreme machine, was developed accurately detect from pool 225 251 healthy subjects....
Discovery of communities in networks is a fundamental data analysis problem. Most the existing approaches have focused on discovering nodes, while recent studies shown great advantages and utilities knowledge links. Stochastic models provides promising class techniques for identification modular structures, but most stochastic mainly focus detection node rather than link communities. We propose model, which not only describes structure communities, also considers heterogeneous distribution...